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Resources

Resources

A repository of data, publications, tools, and other products from project teams, Science Collaborative program, and partners.

Displaying 71 - 80 of 136
Project Overview |

This project overview describes a 2016 Science Transfer project where staff members from the North Carolina National Estuarine Research Reserve are being trained in the application of the CCVATCH tool to assess the vulnerabilities of local coastal habitats to climate change.

Project Overview |

This project overview describes a 2018 Catalyst project that created an Olympia oyster restoration network to enhance the success of West Coast restoration efforts.

Report |

This needs assessment of conservation policy stakeholders in the Pacific Northwest identified data needs and barriers for potential blue carbon project partners.

Multimedia |

This collection of videos uses a hydrodynamic model to show salinity changes in the Coos estuary in different geographies and seasons.

Journal Article |

This article uses a hydrodynamic model of the Coos estuary in southwestern Orgeon to examine seasonal variability of salinity dynamics and estuarine exchange flow.

Project Overview |

This project overview describes a 2018 Catalyst project where researchers from Duke University and the North Carolina and Rookery Bay reserves partnered to develop ecosystem services models for coastal habitats.

Journal Article |

This article discusses changes to the Coos estuary over the past 150 years, and their present and future impacts.

Website |

This website contains data and files to run hydrodynamic modeling simulations for Coos estuary in southwestern Oregon.

Report |

This national synthesis report analyzes SET data from 15 National Estuarine Research Reserves across the continental United States, summarizing wetland water level trends over a 19-year period.

Tool |

A 2018 catalyst project developed tools for working with SET data including a series of computer codes - R scripts - for processing, quality checking, analyzing and visualizing these complex datasets. The statistical codes re available through GitHub and are explained in a Guide to the SETr Workflow.